# load in packages
library(tidyverse)
## Warning: package 'ggplot2' was built under R version 4.2.3
## Warning: package 'tibble' was built under R version 4.2.3
## Warning: package 'dplyr' was built under R version 4.2.3
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.2 ✔ readr 2.1.4
## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ ggplot2 3.4.2 ✔ tibble 3.2.1
## ✔ lubridate 1.9.2 ✔ tidyr 1.3.0
## ✔ purrr 1.0.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
mfn <- 12
'Saras fave food' <- "pizza"
passcode1 <- "password12345678"
Let’s say we had some points data, and wanted to find the distance
set.seed(123)
points <- data.frame(
x = rnorm(10),
y = rnorm(10)
)
# Nested function calculation
sqrt(sum(abs(mean(points$x))))
## [1] 0.2731769
# using objects
mean <- mean(points$x)
abs_mean <- abs(mean)
sum_abs <- sum(abs_mean)
sqrt_sum <- sqrt(sum_abs)
# tidyverse pipes %>%
points$x %>%
mean() %>%
abs() %>%
sum() %>%
sqrt()
## [1] 0.2731769
points %>%
select(x) %>%
mean() %>%
abs() %>%
sum() %>%
sqrt()
## Warning in mean.default(.): argument is not numeric or logical: returning NA
## [1] NA
points$x * points$y %>%
sum()
## [1] -1.1692753 -0.4802008 3.2518078 0.1470960 0.2697226 3.5780022
## [7] 0.9615724 -2.6391956 -1.4329259 -0.9297487
# session ->
# set working directory ->
# to source file location
# need data in same location as your rmd file
#setwd(path) or run code
toenail.txt Text File
student_performance_data.csv Comma Separated Variable File
retail.xlsx Microsoft Excel Worksheet
# all from readr package which we get with tidyverse